Detection of Problem Gambling with Less Features Using Machine Learning Methods

arXiv:2403.15962v1 Announce Type: new
Abstract: Analytic features in gambling study are performed based on the amount of data monitoring on user daily actions. While performing the detection of problem gambling, existing datasets provide relatively rich analytic features for building machine learning based model. However, considering the complexity and cost of collecting the analytic features in real applications, conducting precise detection with less features will tremendously reduce the cost of data collection. In this study, we propose a deep neural networks …

abstract arxiv building complexity cost cs.ai cs.cy cs.lg daily data data monitoring datasets detection features however machine machine learning monitoring study type